U.S. patent application number 16/742180 was filed with the patent office on 2021-07-15 for namespace range creation to distribute workload in a dispersed storage system.
The applicant listed for this patent is INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to Vivek BAJPAI, Thomas DUBUCQ, Kevin Michael FREESE.
Application Number | 20210216513 16/742180 |
Document ID | / |
Family ID | 1000004610272 |
Filed Date | 2021-07-15 |
United States Patent
Application |
20210216513 |
Kind Code |
A1 |
BAJPAI; Vivek ; et
al. |
July 15, 2021 |
NAMESPACE RANGE CREATION TO DISTRIBUTE WORKLOAD IN A DISPERSED
STORAGE SYSTEM
Abstract
A method includes: obtaining, by a computing device, a first
work item from a first index, wherein the first work item
represents a namespace of a bucket of a vault in a dispersed
storage network; dividing, by the computing device, the namespace
into plural ranges of names; creating, by the computing device,
plural second work items, each respective one of the plural second
work items including a respective one of the plural ranges of
names; and adding, by the computing device, each of the plural
second work items to a second index
Inventors: |
BAJPAI; Vivek; (Dekalb,
IL) ; DUBUCQ; Thomas; (Chicago, IL) ; FREESE;
Kevin Michael; (Chicago, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INTERNATIONAL BUSINESS MACHINES CORPORATION |
Armonk |
NY |
US |
|
|
Family ID: |
1000004610272 |
Appl. No.: |
16/742180 |
Filed: |
January 14, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/22 20190101;
G06F 3/0655 20130101; G06F 3/0604 20130101; G06F 3/067
20130101 |
International
Class: |
G06F 16/22 20060101
G06F016/22; G06F 3/06 20060101 G06F003/06 |
Claims
1. A method, comprising: obtaining, by a computing device, a first
work item from a first index, wherein the first work item
represents a namespace of a bucket of a vault in a dispersed
storage network; dividing, by the computing device, the namespace
into plural ranges of names; creating, by the computing device,
plural second work items, each respective one of the plural second
work items including a respective one of the plural ranges of
names; and adding, by the computing device, each of the plural
second work items to a second index.
2. The method of claim 1, wherein the names are names of objects
stored in the dispersed storage network.
3. The method of claim 1, wherein the dividing is performed using a
namespace tree structure and an equation that approximates a same
number of names in each of the plural ranges of names.
4. The method of claim 3, wherein the equation is: number of
objects=((split-size+join-size)/2)*k where: split-size is a maximum
number of objects in a leaf node of the namespace tree structure of
the namespace; join-size is a minimum number of objects in a leaf
node of the namespace tree structure of the namespace; and k is a
number of leaf nodes included in each of the plural second work
items.
5. The method of claim 1, wherein the first work item is included
in the first index based on a determination that the bucket has an
object lifecycle management rule.
6. The method of claim 5, wherein the object lifecycle management
rule defines an action to perform an object that is in the bucket
are that is determined to satisfy one or more conditions, the
action comprising one selected from the group consisting of:
deleting the object; moving the object to a different portion of
the dispersed storage network; and moving the object to a different
storage outside the dispersed storage network.
7. The method of claim 1, wherein the second index is a different
index than the first index.
8. The method of claim 1, wherein: the first index comprises a
first leasable index; and the second index comprises a second
leasable index.
9. The method of claim 1, wherein the computing device is one of
plural dispersed storage processing units in the vault in the
dispersed storage network.
10. The method of claim 9, wherein respective one of the plural
second work items are subsequently leased from the second index by
one of the plural dispersed storage processing units.
11. A computer program product comprising one or more computer
readable storage media having program instructions collectively
stored on the one or more computer readable storage media, the
program instructions executable to: obtain a first work item from a
first leasable index, wherein the first work item represents a
namespace of a bucket of a vault in a dispersed storage network;
divide the namespace into plural ranges of names; create plural
second work items, each respective one of the plural second work
items including a respective one of the plural ranges of names; and
add each of the plural second work items to a second leasable
index.
12. The computer program product of claim 11, wherein the names are
names of objects stored in the dispersed storage network.
13. The computer program product of claim 11, wherein the dividing
is performed using a namespace tree structure and an equation that
includes parameters of the namespace tree structure.
14. The computer program product of claim 11, wherein the first
work item is included in the first index based on a determination
that the bucket has an object lifecycle management rule.
15. The computer program product of claim 11, wherein: the
computing device is one of plural dispersed storage processing
units in the vault in the dispersed storage network; and respective
one of the plural second work items are subsequently leased from
the second index by the one of the plural dispersed storage
processing units or another one of the plural dispersed storage
processing units.
16. A system comprising: a processor, a computer readable memory,
and a computer readable storage medium; program instructions to
lease a first work item from a first leasable index, wherein the
first work item represents a namespace of a bucket in a dispersed
storage network; program instructions to divide the namespace into
plural ranges of names; program instructions to create plural
second work items, each respective one of the plural second work
items including a respective one of the plural ranges of names; and
program instructions to add each of the plural second work items to
a second leasable index, wherein the program instructions are
stored on the computer readable storage medium for execution by the
processor via the computer readable memory.
17. The system of claim 16, wherein the names are names of objects
stored in the dispersed storage network.
18. The system of claim 16, wherein the dividing is performed using
an equation that approximates a same number of names in each of the
plural ranges of names.
19. The system of claim 16, wherein the first work item is included
in the first index based on a determination that the bucket has an
object lifecycle management rule.
20. The system of claim 16, wherein: the computing device is one of
plural dispersed storage processing units in the vault in the
dispersed storage network; and respective one of the plural second
work items are subsequently leased from the second index by the one
of the plural dispersed storage processing units or another one of
the plural dispersed storage processing units.
Description
BACKGROUND
[0001] Aspects of the present invention relate generally to
processing work items in dispersed storage systems and, more
particularly, to systems and methods for performing namespace range
creation to distribute workload in a dispersed storage system.
[0002] Computing devices communicate data, process data, and/or
store data. Such computing devices range from wireless smart
phones, laptops, tablets, personal computers (PC), work stations,
and video game devices, to data centers that support millions of
web searches, stock trades, or on-line purchases every day. In
general, a computing device includes a central processing unit
(CPU), a memory system, user input/output interfaces, peripheral
device interfaces, and an interconnecting bus structure.
[0003] A computer may effectively extend its CPU by using "cloud
computing" to perform one or more computing functions (e.g., a
service, an application, an algorithm, an arithmetic logic
function, etc.) on behalf of the computer. Further, for large
services, applications, and/or functions, cloud computing may be
performed by multiple cloud computing resources in a distributed
manner to improve the response time for completion of the service,
application, and/or function. For example, Hadoop.RTM. is an open
source software framework that supports distributed applications
enabling application execution by thousands of computers.
[0004] In addition to cloud computing, a computer may use "cloud
storage" as part of its memory system. Cloud storage enables a
user, via its computer, to store files, applications, etc., on an
Internet storage system. The Internet storage system may include a
RAID (redundant array of independent disks) system and/or a
dispersed storage system that uses an error correction scheme to
encode data for storage.
SUMMARY
[0005] In a first aspect of the invention, there is a
computer-implemented method including: obtaining, by a computing
device, a first work item from a first index, wherein the first
work item represents a namespace of a bucket of a vault in a
dispersed storage network; dividing, by the computing device, the
namespace into plural ranges of names; creating, by the computing
device, plural second work items, each respective one of the plural
second work items including a respective one of the plural ranges
of names; and adding, by the computing device, each of the plural
second work items to a second index.
[0006] In another aspect of the invention, there is a computer
program product, the computer program product comprising one or
more computer readable storage media having program instructions
collectively stored on the one or more computer readable storage
media, the program instructions executable to: obtain a first work
item from a first leasable index, wherein the first work item
represents a namespace of a bucket of a vault in a dispersed
storage network; divide the namespace into plural ranges of names;
create plural second work items, each respective one of the plural
second work items including a respective one of the plural ranges
of names; and add each of the plural second work items to a second
leasable index.
[0007] In another aspect of the invention, there is system
including a processor, a computer readable memory, and a computer
readable storage medium. The system includes: program instructions
to lease a first work item from a first leasable index, wherein the
first work item represents a namespace of a bucket in a dispersed
storage network; program instructions to divide the namespace into
plural ranges of names; program instructions to create plural
second work items, each respective one of the plural second work
items including a respective one of the plural ranges of names; and
program instructions to add each of the plural second work items to
a second leasable index. The program instructions are stored on the
computer readable storage medium for execution by the processor via
the computer readable memory.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] Aspects of the present invention are described in the
detailed description which follows, in reference to the noted
plurality of drawings by way of non-limiting examples of exemplary
embodiments of the present invention.
[0009] FIG. 1 depicts a cloud computing node according to an
embodiment of the present invention.
[0010] FIG. 2 depicts a cloud computing environment according to an
embodiment of the present invention.
[0011] FIG. 3 depicts abstraction model layers according to an
embodiment of the present invention.
[0012] FIG. 4 shows a dispersed storage network (DSN) in accordance
with aspects of the invention.
[0013] FIG. 5 shows a flowchart of an exemplary method in
accordance with aspects of the invention.
[0014] FIG. 6 shows a block diagram that illustrates operation of
one of the steps in accordance with aspects of the invention.
[0015] FIG. 7 shows an exemplary namespace tree structure and
determining ranges in accordance with aspects of the invention.
[0016] FIG. 8 shows a flowchart of an exemplary method in
accordance with aspects of the invention.
DETAILED DESCRIPTION
[0017] Aspects of the present invention relate generally to
processing work items in dispersed storage systems and, more
particularly, to systems and methods for performing namespace range
creation to distribute workload in a dispersed storage system.
Aspects of the invention are usable in background processes, such
as object lifecycle management processes, in a dispersed storage
network (DSN).
[0018] A user may wish to have a DSN manage the lifecycle of their
data for them. For example the user may want to configure the DSN
to remove data that has reached a certain age, or to remove data
after a certain date. As another example, rather than remove data,
the user may wish to move the data to a lower cost, or lower
performance, storage media. According to aspects of the invention,
a DSN may be organized into multiple buckets, each of which may
have different object lifecycle management rules. In embodiments, a
user may define one or more object lifecycle management rules for a
bucket containing the user's data objects.
[0019] In accordance with aspects of the invention, a DSN has a
generalized mechanism referred to as the Producer Consumer
Scheduler Framework (PCSF) that is configured to perform background
work in dispersed storage systems. This system can be utilized to
create a series of producer/consumer/scheduler bundles that can
implement support for object lifecycle management in the background
of a DSN, e.g., according to the user-defined object lifecycle
management rules that are associated with buckets in the DSN.
[0020] However, the objects names in any given namespace (e.g., for
a particular bucket) are often unequally distributed. For example,
there might be five data objects that begin with the letter "A" and
ninety data objects that begin with the letter "B". The work
distribution for background tasks working on these objects is
difficult, as if the namespace is divided into equal chunks, each
work item can have unequal number of objects to work on. For
example, if a first DSN node processes all the objects beginning
with the letter "A" and a second DSN node processes all the objects
beginning with the letter "B" then there is an uneven distribution
of work between the first DSN node and the second DSN node, and
this leads to inefficiency in processing tasks performed in the
DSN. Also, in such a situation, there can be duplication of work
between DSN nodes, resulting in further inefficiency of the DSN as
a whole.
[0021] Aspects of the invention address this issue by dividing an
internal namespace tree structure (e.g., from an index) into
approximately equal sized pieces, where each piece has a fixed
number of leaf nodes, and adding these pieces to a Distributed
Leasable Tree structure (e.g., another index). In this manner, work
items that are based on the approximately equal sized pieces all
contain approximately the same number of data objects, such that
the work performed in scanning these work items is more evenly
distributed amongst the DSN nodes that perform the work processes.
As such, in an embodiment there is a method for equal work
distribution in a dispersed storage network (DSN) comprising the
steps of: dividing an internal namespace for the DSN into a
plurality of pieces, wherein each piece has a fixed number of leaf
nodes; and adding the plurality of equal pieces to a distributed
leasable tree structure, wherein each of the plurality of equal
pieces can be leased by one or more DS processing units.
[0022] Aspects of the invention improve the functioning of a
computer system by increasing the efficiency of the system and
avoiding duplication of tasks. In particular, aspects of the
invention improve the efficiency of a DSN by evenly distributing
workload amongst plural different DSN nodes that perform background
tasks in the DSN. Aspects of the invention also generate new data
that does not previously exist (e.g., work items containing
approximately equal numbers of object names), and use this new data
in subsequent steps (e.g., adding the work items to a leasable
index from which the work items are leased by DSN nodes to perform
object lifecycle management tasks using the work items).
[0023] The present invention may be a system, a method, and/or a
computer program product at any possible technical detail level of
integration. The computer program product may include a computer
readable storage medium (or media) having computer readable program
instructions thereon for causing a processor to carry out aspects
of the present invention.
[0024] The computer readable storage medium can be a tangible
device that can retain and store instructions for use by an
instruction execution device. The computer readable storage medium
may be, for example, but is not limited to, an electronic storage
device, a magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium
includes the following: a portable computer diskette, a hard disk,
a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a static
random access memory (SRAM), a portable compact disc read-only
memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a
floppy disk, a mechanically encoded device such as punch-cards or
raised structures in a groove having instructions recorded thereon,
and any suitable combination of the foregoing. A computer readable
storage medium or media, as used herein, is not to be construed as
being transitory signals per se, such as radio waves or other
freely propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0025] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0026] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, configuration data for integrated
circuitry, or either source code or object code written in any
combination of one or more programming languages, including an
object oriented programming language such as Smalltalk, C++, or the
like, and procedural programming languages, such as the "C"
programming language or similar programming languages. The computer
readable program instructions may execute entirely on the user's
computer, partly on the user's computer, as a stand-alone software
package, partly on the user's computer and partly on a remote
computer or entirely on the remote computer or server. In the
latter scenario, the remote computer may be connected to the user's
computer through any type of network, including a local area
network (LAN) or a wide area network (WAN), or the connection may
be made to an external computer (for example, through the Internet
using an Internet Service Provider). In some embodiments,
electronic circuitry including, for example, programmable logic
circuitry, field-programmable gate arrays (FPGA), or programmable
logic arrays (PLA) may execute the computer readable program
instructions by utilizing state information of the computer
readable program instructions to personalize the electronic
circuitry, in order to perform aspects of the present
invention.
[0027] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
[0028] These computer readable program instructions may be provided
to a processor of a computer, or other programmable data processing
apparatus to produce a machine, such that the instructions, which
execute via the processor of the computer or other programmable
data processing apparatus, create means for implementing the
functions/acts specified in the flowchart and/or block diagram
block or blocks. These computer readable program instructions may
also be stored in a computer readable storage medium that can
direct a computer, a programmable data processing apparatus, and/or
other devices to function in a particular manner, such that the
computer readable storage medium having instructions stored therein
comprises an article of manufacture including instructions which
implement aspects of the function/act specified in the flowchart
and/or block diagram block or blocks.
[0029] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing
apparatus, or other device to cause a series of operational steps
to be performed on the computer, other programmable apparatus or
other device to produce a computer implemented process, such that
the instructions which execute on the computer, other programmable
apparatus, or other device implement the functions/acts specified
in the flowchart and/or block diagram block or blocks.
[0030] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the blocks may occur out of the order noted in
the Figures. For example, two blocks shown in succession may, in
fact, be accomplished as one step, executed concurrently,
substantially concurrently, in a partially or wholly temporally
overlapping manner, or the blocks may sometimes be executed in the
reverse order, depending upon the functionality involved. It will
also be noted that each block of the block diagrams and/or
flowchart illustration, and combinations of blocks in the block
diagrams and/or flowchart illustration, can be implemented by
special purpose hardware-based systems that perform the specified
functions or acts or carry out combinations of special purpose
hardware and computer instructions.
[0031] It is understood in advance that although this disclosure
includes a detailed description on cloud computing, implementation
of the teachings recited herein are not limited to a cloud
computing environment. Rather, embodiments of the present invention
are capable of being implemented in conjunction with any other type
of computing environment now known or later developed.
[0032] Cloud computing is a model of service delivery for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (e.g. networks, network bandwidth,
servers, processing, memory, storage, applications, virtual
machines, and services) that can be rapidly provisioned and
released with minimal management effort or interaction with a
provider of the service. This cloud model may include at least five
characteristics, at least three service models, and at least four
deployment models.
[0033] Characteristics are as follows:
[0034] On-demand self-service: a cloud consumer can unilaterally
provision computing capabilities, such as server time and network
storage, as needed automatically without requiring human
interaction with the service's provider.
[0035] Broad network access: capabilities are available over a
network and accessed through standard mechanisms that promote use
by heterogeneous thin or thick client platforms (e.g., mobile
phones, laptops, and PDAs).
[0036] Resource pooling: the provider's computing resources are
pooled to serve multiple consumers using a multi-tenant model, with
different physical and virtual resources dynamically assigned and
reassigned according to demand. There is a sense of location
independence in that the consumer generally has no control or
knowledge over the exact location of the provided resources but may
be able to specify location at a higher level of abstraction (e.g.,
country, state, or datacenter).
[0037] Rapid elasticity: capabilities can be rapidly and
elastically provisioned, in some cases automatically, to quickly
scale out and rapidly released to quickly scale in. To the
consumer, the capabilities available for provisioning often appear
to be unlimited and can be purchased in any quantity at any
time.
[0038] Measured service: cloud systems automatically control and
optimize resource use by leveraging a metering capability at some
level of abstraction appropriate to the type of service (e.g.,
storage, processing, bandwidth, and active user accounts). Resource
usage can be monitored, controlled, and reported providing
transparency for both the provider and consumer of the utilized
service.
[0039] Service Models are as follows:
[0040] Software as a Service (SaaS): the capability provided to the
consumer is to use the provider's applications running on a cloud
infrastructure. The applications are accessible from various client
devices through a thin client interface such as a web browser
(e.g., web-based e-mail). The consumer does not manage or control
the underlying cloud infrastructure including network, servers,
operating systems, storage, or even individual application
capabilities, with the possible exception of limited user-specific
application configuration settings.
[0041] Platform as a Service (PaaS): the capability provided to the
consumer is to deploy onto the cloud infrastructure
consumer-created or acquired applications created using programming
languages and tools supported by the provider. The consumer does
not manage or control the underlying cloud infrastructure including
networks, servers, operating systems, or storage, but has control
over the deployed applications and possibly application hosting
environment configurations.
[0042] Infrastructure as a Service (IaaS): the capability provided
to the consumer is to provision processing, storage, networks, and
other fundamental computing resources where the consumer is able to
deploy and run arbitrary software, which can include operating
systems and applications. The consumer does not manage or control
the underlying cloud infrastructure but has control over operating
systems, storage, deployed applications, and possibly limited
control of select networking components (e.g., host firewalls).
[0043] Deployment Models are as follows:
[0044] Private cloud: the cloud infrastructure is operated solely
for an organization. It may be managed by the organization or a
third party and may exist on-premises or off-premises.
[0045] Community cloud: the cloud infrastructure is shared by
several organizations and supports a specific community that has
shared concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
[0046] Public cloud: the cloud infrastructure is made available to
the general public or a large industry group and is owned by an
organization selling cloud services.
[0047] Hybrid cloud: the cloud infrastructure is a composition of
two or more clouds (private, community, or public) that remain
unique entities but are bound together by standardized or
proprietary technology that enables data and application
portability (e.g., cloud bursting for load-balancing between
clouds).
[0048] A cloud computing environment is service oriented with a
focus on statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure comprising a network of interconnected nodes.
[0049] Referring now to FIG. 1, a schematic of an example of a
cloud computing node is shown. Cloud computing node 10 is only one
example of a suitable cloud computing node and is not intended to
suggest any limitation as to the scope of use or functionality of
embodiments of the invention described herein. Regardless, cloud
computing node 10 is capable of being implemented and/or performing
any of the functionality set forth hereinabove.
[0050] In cloud computing node 10 there is a computer system/server
12, which is operational with numerous other general purpose or
special purpose computing system environments or configurations.
Examples of well-known computing systems, environments, and/or
configurations that may be suitable for use with computer
system/server 12 include, but are not limited to, personal computer
systems, server computer systems, thin clients, thick clients,
hand-held or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputer systems, mainframe computer
systems, and distributed cloud computing environments that include
any of the above systems or devices, and the like.
[0051] Computer system/server 12 may be described in the general
context of computer system executable instructions, such as program
modules, being executed by a computer system. Generally, program
modules may include routines, programs, objects, components, logic,
data structures, and so on that perform particular tasks or
implement particular abstract data types. Computer system/server 12
may be practiced in distributed cloud computing environments where
tasks are performed by remote processing devices that are linked
through a communications network. In a distributed cloud computing
environment, program modules may be located in both local and
remote computer system storage media including memory storage
devices.
[0052] As shown in FIG. 1, computer system/server 12 in cloud
computing node 10 is shown in the form of a general-purpose
computing device. The components of computer system/server 12 may
include, but are not limited to, one or more processors or
processing units 16, a system memory 28, and a bus 18 that couples
various system components including system memory 28 to processor
16.
[0053] Bus 18 represents one or more of any of several types of bus
structures, including a memory bus or memory controller, a
peripheral bus, an accelerated graphics port, and a processor or
local bus using any of a variety of bus architectures. By way of
example, and not limitation, such architectures include Industry
Standard Architecture (ISA) bus, Micro Channel Architecture (MCA)
bus, Enhanced ISA (EISA) bus, Video Electronics Standards
Association (VESA) local bus, and Peripheral Component
Interconnects (PCI) bus.
[0054] Computer system/server 12 typically includes a variety of
computer system readable media. Such media may be any available
media that is accessible by computer system/server 12, and it
includes both volatile and non-volatile media, removable and
non-removable media.
[0055] System memory 28 can include computer system readable media
in the form of volatile memory, such as random access memory (RAM)
30 and/or cache memory 32. Computer system/server 12 may further
include other removable/non-removable, volatile/non-volatile
computer system storage media. By way of example only, storage
system 34 can be provided for reading from and writing to a
non-removable, non-volatile magnetic media (not shown and typically
called a "hard drive"). Although not shown, a magnetic disk drive
for reading from and writing to a removable, non-volatile magnetic
disk (e.g., a "floppy disk"), and an optical disk drive for reading
from or writing to a removable, non-volatile optical disk such as a
CD-ROM, DVD-ROM or other optical media can be provided. In such
instances, each can be connected to bus 18 by one or more data
media interfaces. As will be further depicted and described below,
memory 28 may include at least one program product having a set
(e.g., at least one) of program modules that are configured to
carry out the functions of embodiments of the invention.
[0056] Program/utility 40, having a set (at least one) of program
modules 42, may be stored in memory 28 by way of example, and not
limitation, as well as an operating system, one or more application
programs, other program modules, and program data. Each of the
operating system, one or more application programs, other program
modules, and program data or some combination thereof, may include
an implementation of a networking environment. Program modules 42
generally carry out the functions and/or methodologies of
embodiments of the invention as described herein.
[0057] Computer system/server 12 may also communicate with one or
more external devices 14 such as a keyboard, a pointing device, a
display 24, etc.; one or more devices that enable a user to
interact with computer system/server 12; and/or any devices (e.g.,
network card, modem, etc.) that enable computer system/server 12 to
communicate with one or more other computing devices. Such
communication can occur via Input/Output (I/O) interfaces 22. Still
yet, computer system/server 12 can communicate with one or more
networks such as a local area network (LAN), a general wide area
network (WAN), and/or a public network (e.g., the Internet) via
network adapter 20. As depicted, network adapter 20 communicates
with the other components of computer system/server 12 via bus 18.
It should be understood that although not shown, other hardware
and/or software components could be used in conjunction with
computer system/server 12. Examples, include, but are not limited
to: microcode, device drivers, redundant processing units, external
disk drive arrays, RAID systems, tape drives, and data archival
storage systems, etc.
[0058] Referring now to FIG. 2, illustrative cloud computing
environment 50 is depicted. As shown, cloud computing environment
50 comprises one or more cloud computing nodes 10 with which local
computing devices used by cloud consumers, such as, for example,
personal digital assistant (PDA) or cellular telephone 54A, desktop
computer 54B, laptop computer 54C, and/or automobile computer
system 54N may communicate. Nodes 10 may communicate with one
another. They may be grouped (not shown) physically or virtually,
in one or more networks, such as Private, Community, Public, or
Hybrid clouds as described hereinabove, or a combination thereof.
This allows cloud computing environment 50 to offer infrastructure,
platforms and/or software as services for which a cloud consumer
does not need to maintain resources on a local computing device. It
is understood that the types of computing devices 54A-N shown in
FIG. 2 are intended to be illustrative only and that computing
nodes 10 and cloud computing environment 50 can communicate with
any type of computerized device over any type of network and/or
network addressable connection (e.g., using a web browser).
[0059] Referring now to FIG. 3, a set of functional abstraction
layers provided by cloud computing environment 50 (FIG. 2) is
shown. It should be understood in advance that the components,
layers, and functions shown in FIG. 3 are intended to be
illustrative only and embodiments of the invention are not limited
thereto. As depicted, the following layers and corresponding
functions are provided:
[0060] Hardware and software layer 60 includes hardware and
software components. Examples of hardware components include:
mainframes 61; RISC (Reduced Instruction Set Computer) architecture
based servers 62; servers 63; blade servers 64; storage devices 65;
and networks and networking components 66. In some embodiments,
software components include network application server software 67
and database software 68.
[0061] Virtualization layer 70 provides an abstraction layer from
which the following examples of virtual entities may be provided:
virtual servers 71; virtual storage 72; virtual networks 73,
including virtual private networks; virtual applications and
operating systems 74; and virtual clients 75.
[0062] In one example, management layer 80 may provide the
functions described below. Resource provisioning 81 provides
dynamic procurement of computing resources and other resources that
are utilized to perform tasks within the cloud computing
environment. Metering and Pricing 82 provide cost tracking as
resources are utilized within the cloud computing environment, and
billing or invoicing for consumption of these resources. In one
example, these resources may comprise application software
licenses. Security provides identity verification for cloud
consumers and tasks, as well as protection for data and other
resources. User portal 83 provides access to the cloud computing
environment for consumers and system administrators. Service level
management 84 provides cloud computing resource allocation and
management such that required service levels are met. Service Level
Agreement (SLA) planning and fulfillment 85 provide pre-arrangement
for, and procurement of, cloud computing resources for which a
future requirement is anticipated in accordance with an SLA.
[0063] Workloads layer 90 provides examples of functionality for
which the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation 91; software development and
lifecycle management 92; virtual classroom education delivery 93;
data analytics processing 94; transaction processing 95; and
namespace range creation 96.
[0064] Implementations of the invention may include a computer
system/server 12 of FIG. 1 in which one or more of the program
modules 42 are configured to perform (or cause the computer
system/server 12 to perform) one of more functions of the namespace
range creation 96 of FIG. 3. For example, the one or more of the
program modules 42 may be configured to: obtain a first work item
from a first index, wherein the first work item represents a
namespace of a bucket of a vault in a dispersed storage network;
divide the namespace into plural ranges of names; create plural
second work items, each respective one of the plural second work
items including a respective one of the plural ranges of names; and
add each of the plural second work items to a second index.
[0065] FIG. 4 shows a dispersed storage network 400 (DSN) in
accordance with aspects of the invention. In embodiments, the DSN
400 comprises plural dispersed storage processing units 410 (DS
processing units), plural dispersed storage units 420 (DS units),
and at least one dispersed storage manager 430 (DS manager). The DS
processing units 410, the DS units 420, and the DS manager 430 all
communicate via a network 440, which comprises one or more computer
networks such as a LAN, WAN, and the Internet. In a cloud
implementation, the network 440 is a cloud computing environment 50
of FIG. 2, and the DS processing units 410, the DS units 420, and
the DS manager 430 are each nodes 10 in the cloud computing
environment 50.
[0066] In accordance with aspects of the invention, the DSN 400
stores data using object storage technology, which uses Information
Dispersal Algorithms (IDAs) to separate a data object into slices
that are distributed to plural ones of the DS units 420. As used
herein, a slice is a dispersed piece of encoded data. Slices are
created from an original data object and can be used to recreate
the original data object. In particular, the DSN 400 creates slices
using a combination of erasure coding, encryption, and dispersal
algorithms. The erasure coding generates `extra` slices for each
data object, such that the data object can be recreated from a
subset (less than all of) the total number of slices that are
stored for this data object. By dividing a data object into slices
and storing the slices at plural different DS units 420, the DSN
400 ensures that no single one of the DS units 420 has all the
slices that are necessary to recreate the data object. Moreover, by
creating extra slices for each data object, the DSN 400 can
tolerate multiple failures without losing the ability to recreate
the original data object, e.g., from the available slices.
[0067] According to aspects of the invention, the DS manager 430
provides a management interface that is used for system
administrative tasks, such as system configuration, storage
provisioning, and monitoring the health and performance of the
system. The DS manager 430 may comprise a physical device (e.g., a
computer device such as computer system/server 12 of FIG. 1), a
virtual machine (VM), or a container (e.g., a Docker container).
The terms "Docker" and "Hadoop" may be subject to trademark rights
in various jurisdictions throughout the world and are used here
only in reference to the products or services properly denominated
by the marks to the extent that such trademark rights may
exist.
[0068] According to aspects of the invention, the DS processing
units 410 are configured to encrypt and encode data during a write
operation, to manage the dispersal of slices of data during a write
operation, and to decode and decrypt data during a read operation.
In embodiments, the DS processing units 410 are stateless
components that present a storage interface to a client application
and that transform data objects into slices using an IDA. Each DS
processing unit 410 may comprise a physical device (e.g., a
computer device such as a computer system/server 12 of FIG. 1), a
virtual machine (VM), or a container (e.g., a Docker
container).
[0069] According to aspects of the invention, the DS units 420 are
configured to store the data slices that are received from a DS
processing unit 410 during a write, and to return data slices to a
DS processing unit 410 during a read. Each DS unit 420 comprises a
physical device, e.g., a computer storage device such as the
storage system 34 of FIG. 1.
[0070] In implementations, a client device 450 runs a client
application that communicates with one of the DS processing units
410 to perform data operations in the DSN 400. In embodiments, the
client application uses application programming interfaces (APIs)
to perform data operations in the DSN 400. In one example, a first
API call (e.g., PUT) writes a data object to the DSN 400, a second
API call (e.g., GET) reads a data object from the DSN 400, a third
API call (e.g., DELETE) deletes a data object from the DSN 400, and
a fourth API call (e.g., LIST) lists all the data objects in a
bucket in the DSN 400. In embodiments, the client device 450
comprises a computer device such as a laptop computer, desktop
computer, tablet computer, etc., and may comprise one or more
components of the computer system/server 12 of FIG. 1. In
embodiments, the client application running on the client device
450 is a software application, and may comprise one or more program
modules 42 as described with respect to FIG. 1. In embodiments, the
client device 450 communicates with one of the DS processing units
410 via the network 440.
[0071] In embodiments, a vault is a group of DS processing units
410 and DS units 420 in the DSN 400. A vault can be spread across
plural DS units 420, and the DSN 400 may include plural different
vaults. For example, the DSN 400 may include a first vault at a
first geographic location (e.g., Texas), and a second vault at a
second geographic location (e.g., Germany). In embodiments, a
bucket is a logical storage unit of a vault. As used herein, a
bucket is a group of objects stored in a vault that share a same
namespace within the vault, where the namespace is an address
structure used to identify objects in the system. A vault can have
plural different buckets (and, therefore, plural different
namespaces). Each bucket stores one or more objects, e.g., as
plural slices in various ones of the DS units 420 in the vault.
[0072] According to aspects of the invention, each bucket may have
one or more object lifecycle management (OLM) rules that define
certain actions to perform on objects in the bucket when certain
conditions are satisfied. In embodiments, the DSN 400 has an OLM
front-end comprising an API that the client application running on
the client device 450 calls to define OLM rules for a bucket. As
used herein, a rule that is associated with a bucket (also referred
to as a bucket rule or simply a rule) is a data structure that
defines a prescribed action for the DSN 400 to perform on an object
in the bucket when metadata associated with the object satisfies a
condition defined in the rule. Conditions defined in a rule may
include but are not limited to one or more of: matching prefixes;
matching suffixes; the object being older than a predefined age; a
calendar date having been reached; the object was created during a
specific date range; and the amount of space utilized has reached
or exceeded a threshold amount. Actions defined in a rule may
include but are not limited to one or more of: deleting an object
from the DSN 400; moving an object to a different storage medium
within the DSN 400; and moving an object to a different storage
system outside the DSN 400. For example, a rule associated with a
particular bucket might specify that any object (in the bucket)
that is older than 6 months is deleted. As another example, a rule
may specify that all data objects (in the bucket) that begin with
the prefix "/merger" is moved to a different tier of storage after
a date defined by the rule. These examples are not limiting, and
different rules may be used.
[0073] In embodiments, the DSN 400 includes an OLM back-end
comprising plural Producer Consumer Scheduler Framework (PCSF)
bundles that are configured to perform a four stage process
comprising: (i) identify all the buckets within a vault that have a
rule, and generate a first leasable index including work items
corresponding to these buckets; (ii) for each work item in the
first leasable index, divide the namespace of the bucket into
ranges of object names of approximately equal size, and add these
ranges as work items to a second leasable index; (iii) for each
work item in the second leasable index, analyze the object metadata
of each object in the range to identify objects that satisfy the
rule associated with this bucket, and add the identified objects as
work items to a third leasable index; and (iv) for each work item
in the third leasable index, perform the action specified by the
rule associated with this bucket on the object of this work
item.
[0074] This four stage process is illustrated in a flowchart in
FIG. 5 with the steps numbered as 501-504. In embodiments, various
ones of the DS processing units 410 run PCSF bundles that perform
steps 501-504. In a particular embodiment, a single one of the DS
processing units 410 in the DSN 400 performs step 501 to generate a
respective first leasable index for each respective vault in the
DSN 400. Then, in response to receiving the respective first
leasable index for a respective vault, any of plural ones of the DS
processing units 410 in that respective vault perform steps 502,
503, and 504 on identified ones of the buckets in that vault. In
embodiments, step 501 is performed for each vault on a predefined
interval, such as once per day. However, implementations are not
limited to this interval, and other intervals may be used.
[0075] As used herein, a leasable index is a data structure that
contains a queue of work items, where plural DS processing units
410 act in parallel to lease individual ones of the work items and
process the leased work items. In embodiments, when a first DS
processing unit 410 leases a work item from a leasable index, that
work item is marked as "leased" in the leasable index, which
prevents a second one of the DS processing units 410 from leasing
and working on this same work item at the same time as the first DS
processing unit 410. If the first DS processing unit 410 completes
the processing of this work item within a predefined amount of
time, then this work item is deleted from the leasable index. On
the other hand, if the first DS processing unit 410 does not
complete the processing on this work item within the predefined
amount of time, then the lease for this work item expires in the
leasable index, which means that another DS processing unit 410 can
now lease this work item from the leasable index. In this manner,
plural DS processing units 410 work in parallel to lease and
process respective ones of the work items from the leasable index.
In implementations, the contents of the queue of a leasable index
may be in a near constant state of flux, as new work items are
added and existing work items are leased and deleted. In a
particular embodiment, a leasable index is a Dispersed Lockless
Concurrent Index (DLCI).
[0076] FIG. 6 shows a block diagram that illustrates operation of
step 502 of FIG. 5 in accordance with aspects of the invention. In
embodiments, during execution of the OLM background processes
described herein, a first leasable index 605 includes work items
610a, 610b, 610c. Each of these work items 610a, 610b, 610c
represents a namespace of a bucket in this particular vault and
having an OLM rule, e.g., as identified at step 501. According to
aspects of the invention, any one of the DS processing units 410-1,
410-2, 410-3 in this vault can lease one of the work items 610a,
610b, 610c from the first leasable index 605, and process that work
item to generate one or more work items that are added to a second
leasable index 615. In the example shown in FIG. 6, the DS
processing unit 410-1 leases the work item 610b from the first
leasable index 605 and, using the leased work item 610b, the DS
processing unit 410-1 generates work items 620f, 620g, 620h that
are added to the queue of the second leasable index 615 (i.e., the
second leasable index 615 already including work items 620d, 620e).
Although not shown in FIG. 6, work item 610b is then deleted from
the first leasable index 605.
[0077] In accordance with aspects of the invention, each of the
work items 620f, 620g, 620h includes a respective range of names of
objects in the namespace of the bucket associated with work item
610b. In embodiments, the system creates the work items 620f, 620g,
620h using an algorithm that causes each of the work items 620f,
620g, 620h to have approximately the same number of names of
objects in its respective range. In this manner, embodiments of the
invention cause the processing that subsequently occurs at step 503
to be evenly distributed amongst the DS processing units 410-1,
410-2, 410-3 by virtue of the fact that each work item (e.g., 620f,
620g, 620h) that is processed by any one of the DS processing units
410-1, 410-2, 410-3 at step 503 has approximately a same number of
objects to scan.
[0078] In embodiments, each of the DS processing units 410-1,
410-2, 410-3 comprises a range creation module 650 that is
configured to perform step 502 as described herein. The range
creation module 650 may be one or more program modules 42 as
described with respect to FIG. 1. In a particular embodiment, the
range creation module 650 comprises a PCSF bundle that includes a
range creation consumer, a range creation scheduler, and a range
creation consumer, each of which may comprise one or more program
modules 42 as described herein.
[0079] In an exemplary implementation, the range creation module
650 determines the respective ranges of names of objects within
each of the respective work items 620f, 620g, 620h using a
namespace tree structure (of the namespace of the work item from
the first leasable index) and an algorithm that includes parameters
that are used to define the namespace tree structure. In
embodiments, the namespace tree structure is a "B+ tree" data
structure that is used internally by the DSN 400 (e.g., internally
meaning it is not visible to the user at client device 450) to keep
a record of objects in this namespace in order to perform listings
(e.g., LIST) and lookups in an efficient manner.
[0080] An exemplary namespace tree structure 700 is shown in FIG.
7. In embodiments, the namespace tree structure 700 includes a
number of levels equal to "n" with parent nodes at the "n-1" level
and leaf nodes at the "n" level. In embodiments, "split-size" and
"join-size" are parameters that are used to define the nodes in the
namespace tree structure 700, with split-size being defined as the
maximum number of objects in a leaf node, and join-size being the
minimum number of objects in a leaf node. In embodiments, "k" is a
configurable parameter that defines a number of leaf nodes to
include in each work item (e.g., work items 620f, 620g, 620h).
According to aspects of the invention, the range creation module
650 determines a number of objects to include in each range
according to Equation 1.
Number of objects=((split-size+join-size)/2)*k (Equation 1)
[0081] In embodiments, after determining the number of objects to
include in each work item (e.g., work items 620f, 620g, 620h)
according to Equation 1, the range creation module 650 determines
the range of names of objects to include in each work item by
traversing the namespace tree structure 700 in BFS (breadth-first
search) order, and segregating the children nodes of all parent
nodes into the respective work pieces, with "k" number of leaf
nodes per work piece.
[0082] In the example shown in FIG. 7, split-size is set at 500,
join-size is set at 185, and k is set at 3. In this example, the
average number of objects in each leaf node is approximately 343
(e.g., (185+500)/2), and Equation 1 approximates the number of
objects in each work item as 1029. In this example, the system
determines the leaf nodes as follows: leaf node 710-1 contains
objects having names beginning with A through C; leaf node 710-2
contains objects having names beginning with C through CCC; leaf
node 710-3 contains objects having names beginning with CCC through
D; leaf node 710-4 contains objects having names beginning with D
through DD; leaf node 710-5 contains objects having names beginning
with DD through K; leaf node 710-6 contains objects having names
beginning with K through PP; leaf node 710-7 contains objects
having names beginning with PP through R; leaf node 710-8 contains
objects having names beginning with R through V; and leaf node
710-9 contains objects having names beginning with V through Z. In
this example, the range creation module 650 groups leaf nodes
710-1, 710-2, 710-3 into first work item 620f, leaf nodes 710-4,
710-5, 710-6 into second work item 620g, and leaf nodes 710-7,
710-8, 710-9 into third work item 620h. In this example, the first
work item 620f contains a range of object names that begin with A
through D, the second work item 620g contains a range of object
names that begin with D through PP, and the third work item 620h
contains a range of object names that begin with PP through Z.
[0083] FIG. 8 shows a flowchart of an exemplary method in
accordance with aspects of the present invention. Steps of the
method may be carried out in the environment of FIG. 4 and are
described with reference to elements depicted in FIG. 4.
[0084] At step 801, a DS processing unit 410 obtains a first work
item from a first index. In embodiments, and as described herein,
the first index is the first leasable index 605, in which each work
item corresponds to a namespace of a bucket of a vault in a
dispersed storage network. The namespace contains names of objects
stored in this particular bucket. In embodiments, this bucket is
included in the first index based on a determination that the
bucket has an object lifecycle management rule, e.g., as described
at step 501.
[0085] At step 802, the DS processing unit 410 divides the
namespace into plural ranges of names. In embodiments, and as
described herein, the ranges of names are ranges of names of
objects in the bucket. In embodiments, and as described herein, the
dividing is performed using a namespace tree structure and an
equation, such as Equation 1, that approximates a same number of
names in each of the plural ranges of names.
[0086] At step 803, the DS processing unit 410 creates plural
second work items, each respective one of the plural second work
items including a respective one of the plural ranges of names. At
step 804, the DS processing unit 410 adds each of the plural second
work items to a second index. In embodiments, and as described
herein, respective ones of the plural second work items are
subsequently leased from the second index by one of the plural
dispersed storage processing units, for further processing
according to the OLM rule associated with this bucket.
[0087] In embodiments, a service provider could offer to perform
the processes described herein. In this case, the service provider
can create, maintain, deploy, support, etc., the computer
infrastructure that performs the process steps of the invention for
one or more customers. These customers may be, for example, any
business that uses technology. In return, the service provider can
receive payment from the customer(s) under a subscription and/or
fee agreement and/or the service provider can receive payment from
the sale of advertising content to one or more third parties.
[0088] In still additional embodiments, the invention provides a
computer-implemented method, via a network. In this case, a
computer infrastructure, such as computer system/server 12 (FIG.
1), can be provided and one or more systems for performing the
processes of the invention can be obtained (e.g., created,
purchased, used, modified, etc.) and deployed to the computer
infrastructure. To this extent, the deployment of a system can
comprise one or more of: (1) installing program code on a computing
device, such as computer system/server 12 (as shown in FIG. 1),
from a computer-readable medium; (2) adding one or more computing
devices to the computer infrastructure; and (3) incorporating
and/or modifying one or more existing systems of the computer
infrastructure to enable the computer infrastructure to perform the
processes of the invention.
[0089] The descriptions of the various embodiments of the present
invention have been presented for purposes of illustration, but are
not intended to be exhaustive or limited to the embodiments
disclosed. Many modifications and variations will be apparent to
those of ordinary skill in the art without departing from the scope
and spirit of the described embodiments. The terminology used
herein was chosen to best explain the principles of the
embodiments, the practical application or technical improvement
over technologies found in the marketplace, or to enable others of
ordinary skill in the art to understand the embodiments disclosed
herein.
* * * * *